Adaptive and Personalized Assessment Pathways Enabled by GenAI
Abstract
Assessment in higher education is no longer confined to fixed tests, uniform rubrics, or end-point measurement. With the rise of Generative AI, assessment can become more adaptive, dialogic, and responsive to the diverse ways students learn, struggle, and demonstrate understanding. This chapter explores how GenAI can support personalized assessment pathways that adjust tasks, feedback, pacing, and learning evidence according to individual learner needs. Rather than treating assessment as a mechanical process of grading, the chapter frames it as a living pedagogical encounter—one that can guide reflection, reveal hidden misconceptions, and encourage deeper intellectual growth. At the same time, it critically examines concerns around bias, transparency, over-reliance, data ethics, and academic integrity. The chapter argues for a human-centered approach in which GenAI strengthens, rather than replaces, the professional judgment of educators.
